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It is well understood that the performance of machine learning methods is heavily dependent on the choice of data representation (or features) on which they are applied. The rapidly developing field of representation learning is concerned with questions surrounding how we can best learn meaningful and useful representations of data. We take a broad view of the field, and include in it topics such as deep learning and feature learning, metric learning, kernel learning, compositional models, non-linear structured prediction, and issues regarding non-convex optimization.

Despite the importance of representation learning to machine learning and to application areas such as vision, speech, audio and NLP, there is currently no common venue for researchers who share a common interest in this topic. The goal of ICLR is to help fill this void.

ICLR 2013 will be a 3-day event from May 2nd to May 4th 2013, co-located with AISTATS2013 in Scottsdale, Arizona. The conference will adopt a novel publication process, which is explained in further detail here: Publication Model.

The Sixteenth international conference on Artificial Intelligence and Statistics (AISTATS 2013) will be held in Scottsdale, AZ, USA. AISTATS is an interdisciplinary gathering of researchers at the intersection of computer science, artificial intelligence, machine learning, statistics, and related areas. Since its inception in 1985, the primary goal of AISTATS has been to broaden research in these fields by promoting the exchange of ideas among them. We encourage the submission of all papers which are in keeping with this objective.

CVPR is the premier annual Computer Vision event comprising the main CVPR conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers. All of the tutorials and oral presentations will be live streamed.

The workshop was held in Jadwin Hall, Room A10 on the Princeton University campus.

ICRA 2013 Plenary Talks.

Vator (short for innovator) is one of the largest business networks dedicated to high-tech entrepreneurs. Founded and run by veteran and award-winning journalist Bambi Francisco, Vator is an entrepreneur and investor community, with some 100,000 members and high-tech companies. VatorNews is Vator's news site focused on innovation with about 500 contributors.

The Conference for Software User Assistance

Testing

Taught by John Langford and Yann LeCun, this course is for people interested in automatically extracting knowledge from large amounts of data. Students should have some prior knowledge or experience with basic machine learning methods.

You must have taken a machine learning course at the undergraduate or graduate level prior to taking this course, or have industry experience with machine learning.

LxMLS 2012 took place during July 19-25 at Instituto Superior Técnico, a leading Engineering and Science school in Portugal. It is organized jointly by IST, the Instituto de Telecomunicações and the Spoken Language Systems Lab - L2F of INESC-ID. Click here for information about past editions (LxMLS 2011) and to watch the videos of the lectures.

In our second year, the topic of the school is Taming the Social Web.

The school covers a range of machine learning (ML) Topics, from theory to practice, that are important in solving natural language processing (NLP) problems that arise in the analysis and use of Web data.